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HopitAIOpen weights model12B parameters

Hopper 12B benchmarks

All models
  • General rank
    Too few tasks3 non-coding tasks ranked5 needed for a rank
  • Speed#6 / 7
    397 msMedian latency, p50H100 only
  • Cost
    Self-hostedRan on H100No hosted price
  • Scenario judge#1 / 20 tied
    75.5%Best task · Accuracyvs Jev-class models

Comparison summary

Strongest
Judging and evals
Leads 1 of 3 (33%)

Strongest at judging. It is ranked on 3 non-coding tasks, too few for a general rank (5 needed).

Specifications

Lab
HopitAI
Weights
Open weights
Parameters
12B
Licence
Apache-2.0

Judging and evals

Share of tasks led · #9 of 20

  1. ClefLeads 3 of 3
  2. Decision 2.0 Vega 27BLeads 3 of 3
  3. GLiDELeads 3 of 3
  4. Jev-OmniLeads 3 of 3
  5. Kev-27BLeads 3 of 3
  6. WinnowLeads 3 of 3
  7. JevLeads 3 of 6
  8. Hopper 12B
    Leads 1 of 3
See the 3 tasks

LLM-as-a-judge

Tier 2 of 3#9 / 20

Accuracy, % · Higher is better

  1. Decision 2.0 Vega 27B75.5, interval 69.8 to 81.3, tied for the lead
  2. Clef73.0, interval 66.2 to 79.7, tied for the lead
  3. Jev72.5, interval 66.7 to 78.3, tied for the lead
  4. GLiDE72.0, interval 65.7 to 78.1, tied for the lead
  5. Jev-Omni72.0, interval 65.5 to 78.5, tied for the lead
  6. Kev-27B72.0, interval 65.6 to 78.4, tied for the lead
  7. DiffusionGemma-Jev70.5, interval 63.8 to 77.4, tied for the lead
  8. Hopper 12B
    65.0, interval 57.8 to 71.6, tier 2
Tested against Jev and 18 Jev-class models

Scenario judge

Tied for the lead#1 / 20

Accuracy, % · Higher is better

  1. Clef83.0, interval 77.4 to 88.4, tied for the lead
  2. Decision 2.0 Vega 27B81.0, interval 75.5 to 86.1, tied for the lead
  3. GLiDE79.5, interval 74.4 to 84.7, tied for the lead
  4. Winnow79.0, interval 73.1 to 85.0, tied for the lead
  5. Kev-27B78.0, interval 71.6 to 84.0, tied for the lead
  6. Jev76.5, interval 70.4 to 82.1, tied for the lead
  7. Hopper 12B
    75.5, interval 69.5 to 81.5, tied for the lead
  8. Jev-Omni75.5, interval 69.3 to 81.7, tied for the lead
Tested against Jev and 18 Jev-class models

Search

Tier 2 of 4#8 / 20

Accuracy, % · Higher is better

  1. Jev-Omni72.5, interval 65.7 to 78.7, tied for the lead
  2. GLiDE71.5, interval 64.4 to 77.8, tied for the lead
  3. Decision 2.0 Vega 27B71.0, interval 64.5 to 77.0, tied for the lead
  4. Winnow69.5, interval 63.2 to 75.6, tied for the lead
  5. Jev69.0, interval 62.3 to 75.5, tied for the lead
  6. Clef67.5, interval 61.3 to 73.1, tied for the lead
  7. Kev-27B66.0, interval 59.7 to 71.8, tied for the lead
  8. Hopper 12B
    57.0, interval 50.5 to 63.2, tier 2
Tested against Jev and 18 Jev-class models

Speed

Median latency, p50 · H100 only · lower is better

  1. Cygnet162 ms
  2. DiffusionGemma-Jev188 ms
  3. Decision 2.0 Lux 9B213 ms
  4. Jev-Omni248 ms
  5. Kev-27B318 ms
  6. Hopper 12B
    397 ms
  7. Decision 2.0 Vega 27B724 ms
How we count

A model leads a task when it is in the task's leading tie tier. Each task counts inside its own benchmark, against that benchmark's models; no score is averaged. An area chart shows the models ranked on at least 2 of the area's tasks in a benchmark this model is in too. The overall standing counts every non-coding tasks and needs 5 for a rank. Latency is compared only on one hardware tier.

Hopper 12BOther modelsWhisker: 95% interval